Micheal Lanham

Micheal Lanham is a distinguished software and technology innovator with more than two decades of experience in the industry. He has an extensive background in developing various software applications across several domains, such as gaming, graphics, web development, desktop engineering, AI, GIS, oil and gas geoscience/geomechanics, and machine learning. Micheal began by pioneering work in integrating neural networks and evolutionary algorithms into game development, which began around the turn of the millennium. He has authored multiple influential books exploring deep learning, game development, and augmented reality, including Evolutionary Deep Learning (Manning, 2023) and Augmented Reality Game Development (Packt Publishing, 2017). He has contributed to the tech community via publications with many significant tech publishers, including Manning. Micheal resides in Calgary, Alberta, Canada, with his large family, whom he enjoys cooking for.

books & videos by Micheal Lanham

AI Agents in Action Video Edition
Included with a Manning Online subscription

In AI Agents in Action, you’ll learn how to build production-ready assistants, multi-agent systems, and behavioral agents. You’ll master the essential parts of an agent, including retrieval-augmented knowledge and memory, while you create multi-agent applications that can use software tools, plan tasks autonomously, and learn from experience. As you explore the many interesting examples, you’ll work with state-of-the-art tools like OpenAI Assistants API, GPT Nexus, LangChain, Prompt Flow, AutoGen, and CrewAI.

AI Agents in Action, Second Edition
  • MEAP began November 2025
  • Last updated November 2025
  • Publication in Spring 2026 (estimated)
  • ISBN 9781633434530
  • 325 pages (estimated)
Included with a Manning Online subscription
  • printed in black & white
catalog / Data Science / AI / AI Agents

AI Agents in Action, Second Edition provides a solid foundation for readers just starting with agents, and it also introduces more advanced techniques and tools for experienced AI developers. You’ll work through the core layers of an agentic system, including prompt engineering, working with tools, reasoning and planning, knowledge and memory, evaluation, and feedback patterns. Each chapter combines practical, real-world examples that cover reasoning frameworks like ReAct and Sequential Thinking MCP, advanced RAG systems, and multi-agent collaboration patterns. Plus, you’ll find extensive tips, tricks, and best practice advice taken from Micheal Lanham’s extensive AI career.